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Shashank Suhas
seminar-breakout
Commits
589a8a35
Commit
589a8a35
authored
Jan 23, 2017
by
Yuxin Wu
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make progressbar a callback
parent
a59e46cd
Changes
6
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6 changed files
with
59 additions
and
28 deletions
+59
-28
scripts/dump-model-params.py
scripts/dump-model-params.py
+1
-2
tensorpack/callbacks/base.py
tensorpack/callbacks/base.py
+18
-8
tensorpack/callbacks/stats.py
tensorpack/callbacks/stats.py
+2
-1
tensorpack/callbacks/steps.py
tensorpack/callbacks/steps.py
+18
-3
tensorpack/train/base.py
tensorpack/train/base.py
+14
-10
tensorpack/train/config.py
tensorpack/train/config.py
+6
-4
No files found.
scripts/dump-model-params.py
View file @
589a8a35
...
@@ -10,7 +10,6 @@ import imp
...
@@ -10,7 +10,6 @@ import imp
from
tensorpack
import
TowerContext
,
logger
,
ModelFromMetaGraph
from
tensorpack
import
TowerContext
,
logger
,
ModelFromMetaGraph
from
tensorpack.tfutils
import
sessinit
,
varmanip
from
tensorpack.tfutils
import
sessinit
,
varmanip
from
tensorpack.utils.naming
import
EXTRA_SAVE_VARS_KEY
parser
=
argparse
.
ArgumentParser
()
parser
=
argparse
.
ArgumentParser
()
parser
.
add_argument
(
'--config'
,
help
=
'config file'
)
parser
.
add_argument
(
'--config'
,
help
=
'config file'
)
...
@@ -44,7 +43,7 @@ with tf.Graph().as_default() as G:
...
@@ -44,7 +43,7 @@ with tf.Graph().as_default() as G:
varmanip
.
dump_session_params
(
args
.
output
)
varmanip
.
dump_session_params
(
args
.
output
)
else
:
else
:
var
=
tf
.
get_collection
(
tf
.
GraphKeys
.
TRAINABLE_VARIABLES
)
var
=
tf
.
get_collection
(
tf
.
GraphKeys
.
TRAINABLE_VARIABLES
)
var
.
extend
(
tf
.
get_collection
(
EXTRA_SAVE_VARS_KEY
))
var
.
extend
(
tf
.
get_collection
(
tf
.
GraphKeys
.
MODEL_VARIABLES
))
var_dict
=
{}
var_dict
=
{}
for
v
in
var
:
for
v
in
var
:
name
=
varmanip
.
get_savename_from_varname
(
v
.
name
)
name
=
varmanip
.
get_savename_from_varname
(
v
.
name
)
...
...
tensorpack/callbacks/base.py
View file @
589a8a35
...
@@ -15,9 +15,10 @@ class Callback(object):
...
@@ -15,9 +15,10 @@ class Callback(object):
""" Base class for all callbacks
""" Base class for all callbacks
Attributes:
Attributes:
epoch_num(int): the number of epochs that have completed the update
epoch_num(int): the epoch that have completed the update.
trainer(Trainer): the trainer
step_num(int): the step number in the current epoch.
graph(tf.Graph): the graph
trainer(Trainer): the trainer.
graph(tf.Graph): the graph.
Note:
Note:
These attributes are available only after (and including)
These attributes are available only after (and including)
...
@@ -34,7 +35,6 @@ class Callback(object):
...
@@ -34,7 +35,6 @@ class Callback(object):
"""
"""
self
.
trainer
=
trainer
self
.
trainer
=
trainer
self
.
graph
=
tf
.
get_default_graph
()
self
.
graph
=
tf
.
get_default_graph
()
self
.
epoch_num
=
self
.
trainer
.
config
.
starting_epoch
-
1
with
tf
.
name_scope
(
type
(
self
)
.
__name__
):
with
tf
.
name_scope
(
type
(
self
)
.
__name__
):
self
.
_setup_graph
()
self
.
_setup_graph
()
...
@@ -91,7 +91,6 @@ class Callback(object):
...
@@ -91,7 +91,6 @@ class Callback(object):
"""
"""
Triggered after every epoch.
Triggered after every epoch.
"""
"""
self
.
epoch_num
+=
1
self
.
_trigger_epoch
()
self
.
_trigger_epoch
()
def
_trigger_epoch
(
self
):
def
_trigger_epoch
(
self
):
...
@@ -106,6 +105,14 @@ class Callback(object):
...
@@ -106,6 +105,14 @@ class Callback(object):
def
_after_train
(
self
):
def
_after_train
(
self
):
pass
pass
@
property
def
epoch_num
(
self
):
return
self
.
trainer
.
epoch_num
@
property
def
step_num
(
self
):
return
self
.
trainer
.
step_num
def
__str__
(
self
):
def
__str__
(
self
):
return
type
(
self
)
.
__name__
return
type
(
self
)
.
__name__
...
@@ -128,12 +135,15 @@ class ProxyCallback(Callback):
...
@@ -128,12 +135,15 @@ class ProxyCallback(Callback):
def
_setup_graph
(
self
):
def
_setup_graph
(
self
):
self
.
cb
.
setup_graph
(
self
.
trainer
)
self
.
cb
.
setup_graph
(
self
.
trainer
)
def
_after_train
(
self
):
self
.
cb
.
after_train
()
def
_trigger_epoch
(
self
):
def
_trigger_epoch
(
self
):
self
.
cb
.
trigger_epoch
()
self
.
cb
.
trigger_epoch
()
def
_trigger_step
(
self
,
*
args
):
self
.
cb
.
trigger_step
(
*
args
)
def
_after_train
(
self
):
self
.
cb
.
after_train
()
def
__str__
(
self
):
def
__str__
(
self
):
return
"Proxy-"
+
str
(
self
.
cb
)
return
"Proxy-"
+
str
(
self
.
cb
)
...
...
tensorpack/callbacks/stats.py
View file @
589a8a35
...
@@ -112,7 +112,8 @@ class StatHolder(object):
...
@@ -112,7 +112,8 @@ class StatHolder(object):
class
StatPrinter
(
Callback
):
class
StatPrinter
(
Callback
):
"""
"""
A callback to control what stats to print. Print everything by default.
A callback to control what stats to print. Enable by default to print
everything in trainer.stat_holder.
"""
"""
def
__init__
(
self
,
print_tag
=
None
):
def
__init__
(
self
,
print_tag
=
None
):
...
...
tensorpack/callbacks/steps.py
View file @
589a8a35
...
@@ -8,13 +8,14 @@
...
@@ -8,13 +8,14 @@
import
tensorflow
as
tf
import
tensorflow
as
tf
import
re
import
re
from
six.moves
import
zip
from
six.moves
import
zip
import
tqdm
from
..utils
import
logger
from
..utils
import
logger
,
get_tqdm_kwargs
from
..utils.naming
import
MOVING_SUMMARY_VARS_KEY
from
..utils.naming
import
MOVING_SUMMARY_VARS_KEY
from
..tfutils.common
import
get_op_tensor_name
,
get_global_step_var
from
..tfutils.common
import
get_op_tensor_name
,
get_global_step_var
from
.base
import
Callback
from
.base
import
Callback
__all__
=
[
'StepStatPrinter'
,
'SummaryMovingAverage'
]
__all__
=
[
'StepStatPrinter'
,
'SummaryMovingAverage'
,
'ProgressBar'
]
class
StepStatPrinter
(
Callback
):
class
StepStatPrinter
(
Callback
):
...
@@ -38,7 +39,7 @@ class StepStatPrinter(Callback):
...
@@ -38,7 +39,7 @@ class StepStatPrinter(Callback):
class
SummaryMovingAverage
(
Callback
):
class
SummaryMovingAverage
(
Callback
):
""" Maintain the moving average of the tensors
""" Maintain the moving average of the tensors
in every step, and summarize them.
in every step, and summarize them.
Enabled by default.
"""
"""
def
__init__
(
self
,
collection
=
MOVING_SUMMARY_VARS_KEY
,
decay
=
0.95
):
def
__init__
(
self
,
collection
=
MOVING_SUMMARY_VARS_KEY
,
decay
=
0.95
):
"""
"""
...
@@ -65,3 +66,17 @@ class SummaryMovingAverage(Callback):
...
@@ -65,3 +66,17 @@ class SummaryMovingAverage(Callback):
def
_extra_fetches
(
self
):
def
_extra_fetches
(
self
):
return
[
self
.
ema_op
]
return
[
self
.
ema_op
]
class
ProgressBar
(
Callback
):
""" A progress bar based on tqdm. Enabled by default. """
def
_before_train
(
self
):
self
.
_total
=
self
.
trainer
.
config
.
step_per_epoch
self
.
_tqdm_args
=
get_tqdm_kwargs
(
leave
=
True
)
def
_trigger_step
(
self
,
*
args
):
if
self
.
step_num
==
0
:
self
.
_bar
=
tqdm
.
trange
(
self
.
_total
,
**
self
.
_tqdm_args
)
self
.
_bar
.
update
()
if
self
.
step_num
==
self
.
_total
-
1
:
self
.
_bar
.
__exit__
()
tensorpack/train/base.py
View file @
589a8a35
...
@@ -7,11 +7,10 @@ import re
...
@@ -7,11 +7,10 @@ import re
import
weakref
import
weakref
import
six
import
six
from
six.moves
import
range
from
six.moves
import
range
import
tqdm
import
tensorflow
as
tf
import
tensorflow
as
tf
from
.config
import
TrainConfig
from
.config
import
TrainConfig
from
..utils
import
logger
,
get_tqdm_kwargs
from
..utils
import
logger
from
..utils.timer
import
timed_operation
from
..utils.timer
import
timed_operation
from
..callbacks
import
StatHolder
from
..callbacks
import
StatHolder
from
..tfutils
import
get_global_step
,
get_global_step_var
from
..tfutils
import
get_global_step
,
get_global_step_var
...
@@ -33,14 +32,18 @@ class Trainer(object):
...
@@ -33,14 +32,18 @@ class Trainer(object):
""" Base class for a trainer.
""" Base class for a trainer.
Attributes:
Attributes:
stat_holder (StatHolder)
summary_writer (tf.summary.FileWriter)
summary_op (tf.Operation): an Op which outputs all summaries.
config (TrainConfig): the config used in this trainer.
config (TrainConfig): the config used in this trainer.
model (ModelDesc)
model (ModelDesc)
sess (tf.Session): the current session in use.
sess (tf.Session): the current session in use.
coord (tf.train.Coordinator)
coord (tf.train.Coordinator)
stat_holder (StatHolder)
summary_writer (tf.summary.FileWriter)
summary_op (tf.Operation): an Op which outputs all summaries.
extra_fetches (list): list of tensors/ops to fetch by :meth:`run_step`.
extra_fetches (list): list of tensors/ops to fetch by :meth:`run_step`.
epoch_num (int): the current epoch number.
step_num (int): the current step number (in an epoch).
"""
"""
def
__init__
(
self
,
config
):
def
__init__
(
self
,
config
):
...
@@ -54,6 +57,9 @@ class Trainer(object):
...
@@ -54,6 +57,9 @@ class Trainer(object):
self
.
sess
=
tf
.
Session
(
config
=
self
.
config
.
session_config
)
self
.
sess
=
tf
.
Session
(
config
=
self
.
config
.
session_config
)
self
.
coord
=
tf
.
train
.
Coordinator
()
self
.
coord
=
tf
.
train
.
Coordinator
()
self
.
epoch_num
=
self
.
config
.
starting_epoch
self
.
step_num
=
0
def
train
(
self
):
def
train
(
self
):
""" Start training """
""" Start training """
self
.
setup
()
self
.
setup
()
...
@@ -165,15 +171,13 @@ class Trainer(object):
...
@@ -165,15 +171,13 @@ class Trainer(object):
try
:
try
:
callbacks
.
before_train
()
callbacks
.
before_train
()
logger
.
info
(
"Start training with global_step={}"
.
format
(
get_global_step
()))
logger
.
info
(
"Start training with global_step={}"
.
format
(
get_global_step
()))
for
epoch_num
in
range
(
for
self
.
epoch_num
in
range
(
self
.
config
.
starting_epoch
,
self
.
config
.
max_epoch
+
1
):
self
.
config
.
starting_epoch
,
self
.
config
.
max_epoch
+
1
):
with
timed_operation
(
with
timed_operation
(
'Epoch {} (global_step {})'
.
format
(
'Epoch {} (global_step {})'
.
format
(
epoch_num
,
get_global_step
()
+
self
.
config
.
step_per_epoch
),
self
.
epoch_num
,
get_global_step
()
+
self
.
config
.
step_per_epoch
),
log_start
=
True
):
log_start
=
True
):
for
step
in
tqdm
.
trange
(
for
self
.
step_num
in
range
(
self
.
config
.
step_per_epoch
):
self
.
config
.
step_per_epoch
,
**
get_tqdm_kwargs
(
leave
=
True
)):
if
self
.
coord
.
should_stop
():
if
self
.
coord
.
should_stop
():
return
return
fetch_data
=
self
.
run_step
()
# implemented by subclass
fetch_data
=
self
.
run_step
()
# implemented by subclass
...
...
tensorpack/train/config.py
View file @
589a8a35
...
@@ -4,7 +4,9 @@
...
@@ -4,7 +4,9 @@
import
tensorflow
as
tf
import
tensorflow
as
tf
from
..callbacks
import
Callbacks
,
SummaryMovingAverage
,
StatPrinter
from
..callbacks
import
(
Callbacks
,
SummaryMovingAverage
,
StatPrinter
,
ProgressBar
)
from
..dataflow.base
import
DataFlow
from
..dataflow.base
import
DataFlow
from
..models
import
ModelDesc
from
..models
import
ModelDesc
from
..utils
import
logger
from
..utils
import
logger
...
@@ -38,8 +40,8 @@ class TrainConfig(object):
...
@@ -38,8 +40,8 @@ class TrainConfig(object):
callbacks (list): a list of :class:`Callback` to perform during training.
callbacks (list): a list of :class:`Callback` to perform during training.
extra_callbacks (list): the same as ``callbacks``. This argument
extra_callbacks (list): the same as ``callbacks``. This argument
is only used to provide the defaults. The defaults are
is only used to provide the defaults. The defaults are
``[SummaryMovingAverage(), StatPrinter()]``. The list of
``[SummaryMovingAverage(),
ProgressBar(),
StatPrinter()]``. The list of
callbacks that will be used in the end
is
``callbacks + extra_callbacks``.
callbacks that will be used in the end
are
``callbacks + extra_callbacks``.
session_config (tf.ConfigProto): the config used to instantiate the session.
session_config (tf.ConfigProto): the config used to instantiate the session.
session_init (SessionInit): how to initialize variables of a session. Defaults to a new session.
session_init (SessionInit): how to initialize variables of a session. Defaults to a new session.
starting_epoch (int): The index of the first epoch.
starting_epoch (int): The index of the first epoch.
...
@@ -80,7 +82,7 @@ class TrainConfig(object):
...
@@ -80,7 +82,7 @@ class TrainConfig(object):
callbacks
=
callbacks
.
cbs
[:
-
1
]
# the last one is StatPrinter()
callbacks
=
callbacks
.
cbs
[:
-
1
]
# the last one is StatPrinter()
assert_type
(
callbacks
,
list
)
assert_type
(
callbacks
,
list
)
if
extra_callbacks
is
None
:
if
extra_callbacks
is
None
:
extra_callbacks
=
[
SummaryMovingAverage
(),
StatPrinter
()]
extra_callbacks
=
[
SummaryMovingAverage
(),
ProgressBar
(),
StatPrinter
()]
self
.
callbacks
=
callbacks
+
extra_callbacks
self
.
callbacks
=
callbacks
+
extra_callbacks
assert_type
(
self
.
callbacks
,
list
)
assert_type
(
self
.
callbacks
,
list
)
self
.
callbacks
=
Callbacks
(
self
.
callbacks
)
self
.
callbacks
=
Callbacks
(
self
.
callbacks
)
...
...
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